Open AccessA Research on Online Grammar Checker System Based on Neural Network Model
Author(s) -
Senyue Hao,
Gang Hao
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1651/1/012135
Subject(s) - computer science , grammar , natural language processing , artificial intelligence , affix grammar , attribute grammar , grammar induction , focus (optics) , regular grammar , programming language , emergent grammar , linguistics , generative grammar , rule based machine translation , philosophy , physics , optics
Grammar error correction is one of the most important research fields in natural language processing, while grammar checker is the tool to help people correct grammatical error. We focus our work on researching a better approach to an online grammar checker system to help people correct the grammatical error in their text more precisely, user-friendly, and efficiently. This new method of online grammar checker system is based on neural network model, Transformer, and is able to detect about 25 different types of grammatical errors in the text. We did the evaluation on our new online grammar checker system, and the final experiment results proved that we have found a good approach to the online grammar checker system.